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JOURNALS // Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki // Archive

Zh. Vychisl. Mat. Mat. Fiz., 2025 Volume 65, Number 7, Pages 1143–1155 (Mi zvmmf12009)

General numerical methods

K-optimal preconditioners based on approximations of inverse matrices

I. V. Oseledetsabc, E. A. Muravlevabd

a Artificial Intelligence Research Institute, Moscow
b Skolkovo Institute of Science and Technology
c Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow
d Sberbank AI Center for Science, Moscow, Russia

Abstract: The problem of constructing preconditioners of a special kind for solving systems of linear algebraic equations is considered. A new approach to the construction of preconditioners based on minimizing the K-number of conditionality for the $A^{-1}P$ matrix is proposed, where $A$ is the initial matrix of the system, $P$ is the preconditioner. It is proved that for circulant matrices, this approach is equivalent to constructing an optimal Chen circulant for the inverse matrix. Numerical experiments have been carried out on a series of test problems with Toeplitz matrices, showing that the proposed approach makes it possible to significantly reduce the number of iterations of the conjugate gradient method compared with the classical approach. The results obtained open up new possibilities for constructing effective preconditioners in other classes of matrices.

Key words: preconditioners, circulant matrices, K-optimality.

UDC: 519.612

Received: 03.02.2025
Accepted: 23.04.2025

DOI: 10.31857/S0044466925070063


 English version:
Computational Mathematics and Mathematical Physics, 2025, 65:7, 1535–1547

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© Steklov Math. Inst. of RAS, 2025